Assessing Understory Complexity in Beech-dominated Forests (Fagus sylvatica L.) in Central Europe—From Managed to Primary Forests

Abstract

Understory vegetation influences several ecosystem services and functions of European beech (Fagus sylvatica L.) forests. Despite this knowledge on the importance of understory vegetation, it is still difficult to measure its three-dimensional characteristics in a quantitative manner. With the recent advancements in terrestrial laser scanning (TLS), we now have the means to analyze detailed spatial patterns of forests. Here, we present a new measure to quantify understory complexity. We tested the approach for different management types, ranging from traditionally and alternatively managed forests and national parks in Germany to primary forests of Eastern Europe and the Ukraine, as well as on an inventory site with more detailed understory reference data. The understory complexity index (UCI) was derived from point clouds from single scans and tested for its relationship with forest management and conventional inventory data. Our results show that advanced tree regeneration is a strong driver of the UCI. Furthermore, the newly developed index successfully measured understory complexity of differently managed beech stands and was able to distinguish scanning positions located on and away from skid-trails in managed stands. The approach enables a deeper understanding of the complexity of understory structures of forests and their drivers and dependents.

Predicting Tree-Related Microhabitats by Multisensor Close-Range Remote Sensing Structural Parameters for the Selection of Retention Elements

“…Rehush et al [38] detected TreMs only on the stem section and just for beech (Fagus sylvatica L.) trees with advanced machine learning techniques and were able to detect those TreMs with an accuracy of up to 83%. However, close-range remote sensing techniques are able to describe small-scale structural complexity of forests in increasing detail [4,[39][40][41][42]. TreM inventories and RS techniques are often used to answer similar research questions, for instance the quantification of old-growth attributes in forests [39,43] and the selection of habitat trees [32,44].…”

Analyzing Spatial Distribution Patterns of European Beech (Fagus sylvatica L.) Regeneration in Dependence of Canopy Openings

“…The other was in Uholka in the Ukrainian Uholka-Shyrokoluzhansky area, belonging to the Carpathian Biosphere Reserve. More information on the sites can be found in Stiers et al [35] and Willim et al [36]. [35]) in relation to the potential natural vegetation (grey) of European beech without human influence according to the European Forest Genetic Resources Programme (EUFORGEN) [37].…”

“…Within the selected stands, canopy gaps and associated regeneration patches were detected and recorded following pre-defined transect lines [35,36]. To ensure comparability between different regeneration patches, the age of the regeneration was estimated by counting internodes and was not to exceed 10-15 years.…”

“…Using phase-difference technology Stiers et al [35]) in relation to the potential natural vegetation (grey) of European beech without human influence according to the European Forest Genetic Resources Programme (EUFORGEN) [37]. Within the selected stands, canopy gaps and associated regeneration patches were detected and recorded following pre-defined transect lines [35,36]. To ensure comparability between different regeneration patches, the age of the regeneration was estimated by counting internodes and was not to exceed 10-15 years.…”

Beech forests as world heritage in aspect to the next extension of the ancient and primeval beech forests of the Carpathians and other regions of Europe world heritage site

“…Since nature protection and close-to-nature forest management are gaining more recognition in Europe, the awareness of the significance of such undisturbed forests as reference sites has arisen, for they provide insight into the structure and development of natural forests to accommodate the ecologically-based forest management (Diaci, 1999;Willim et al 2019;Christensen et al 2005;Vandekerkhove et al 2009;Rugani et al 2013;Bengtsson et al 2000).…”